Top 22 BP Data Analyst Interview Questions + Guide in 2024

BP, a global energy giant, has crossed over $15 billion in profit in 2023. Despite struggling with reduced fossil fuel consumption, BP has rebounded with sustainability efforts and robust management strategies.

Fueled by the efforts of data analysts, improved operational efficiency and better marketing campaigns have contributed to BP’s present financial excellence. Your curiosity in the interview process for the role is natural, given the high-stakes responsibilities you’ll have as a data analyst at BP. We’ll cover what you need to know in this article including sample BP data analyst interview questions.

BP employs data analysts across various departments, including finance, staff, marketing, and operations. Your technical and behavioral specializations will be evaluated during the data analyst interview to verify your belief that you are the right one for the team.

BP follows a structural interview process that allows interviewers to ascertain your applied, communicational, and technical skills.

Applying for the Data Analyst Role

The application process for the data analyst role at BP starts with their career portal, where you can apply. However, you’re more likely to continue if a BP recruiter encourages you to apply for the available data analyst role.

Your contact details, CV, and answers to questions related to SQL and analytics will determine your success in this stage of the data analyst interview.

A specialized talent acquisition team and your hiring manager will screen the applications and shortlist the CVs to proceed to the next stage.

Telephone/Video Screening Round

If you are among the successful applicants, your contact from the talent acquisition team will invite you to a short telephone/video interview. During the call, they’ll ask you a few behavioral questions and some regarding your experience as a data analyst. Multiple stakeholders may join the video interview to conduct the screening process.

As technical questions are rarely asked during this stage, these calls assess your experience, communication skills, and alignment with BP’s cultural beliefs.

Technical Telephonic/Video Round

Your proficiency in SQL for data querying and manipulation will predominantly be tested during the telephone/video round. This phase will also assess your experience with data analysis and visualization tools, such as pandas, NumPy, Tableau, and R.

Additionally, take-home scenario-based challenges may be assigned to evaluate your technical prowess as a potential data analyst at BP.

Face-to-Face Interview Stage

Next, you may be invited to the on-site or face-to-face interview stage, where you’ll meet your hiring manager and some potential colleagues. The hiring manager and other stakeholders are likely to conduct multiple rounds of interviews going deeper into the technical and behavioral aspects of the job.

As a data analyst candidate, if your expertise aligns with BP’s requirements, they’ll confirm your employment within a week or two via a call and email.

BP demands remarkable, scalable technical skills from its data analysts. Your alignment with their purpose and beliefs will also contribute to a successful interview experience. In this section, we’ve gathered a few common BP data analyst interview questions and curated ideal answers for you.

1. What would your current manager say about you? What constructive criticisms might he give?

Your interviewer at BP may ask this question to understand how you perceive yourself and how you could improve as a data analyst.

How to Answer

Reflect on feedback you’ve received from your manager, focusing on both positive aspects and areas for improvement. Emphasize your strengths while acknowledging areas you’re actively working to improve.

Example

“If asked, my current manager would likely highlight my strong analytical skills and ability to deliver results under pressure. However, they might also mention my occasional tendency to dive too deeply into details, which sometimes delays decision-making. I’ve been actively working on balancing this by improving my time management and prioritization skills.”

2. What makes you a good fit for BP?

This question evaluates your understanding of BP’s values and culture and the specific skills and experiences you bring to the table.

How to Answer

Highlight relevant skills, experiences, and values that align with BP’s mission and culture. Demonstrate an understanding of BP’s industry and challenges and how your background can contribute to addressing them.

Example

“I believe my background in data analysis, particularly in the energy sector, aligns well with BP’s focus on innovation and sustainability. My experience in using data to drive strategic decision-making and optimize processes could contribute significantly to BP’s initiatives in renewable energy and environmental sustainability.”

3. Tell me about a time when you exceeded expectations during a project. What did you do, and how did you accomplish it?

Your ability as a data analyst to perform beyond what’s expected and your problem-solving skills will be evaluated with this question.

How to Answer

Describe a project for which you went above and beyond, detailing the challenges you faced, actions you took, and outcomes achieved. Highlight your initiative, creativity, and ability to collaborate.

Example

“In a recent project, we faced tight deadlines and unexpected data discrepancies. I took the initiative to streamline data collection processes and collaborated closely with team members to identify and address issues quickly. Using automation tools and encouraging open communication, we met the deadline and exceeded client expectations. In turn, we received positive feedback and additional project opportunities.”

4. How do you prioritize tasks and stay organized when you have multiple deadlines?

You’re being asked to demonstrate time management and organizational skills, crucial in a fast-paced environment like BP. They want to know how you manage competing priorities.

How to Answer

Explain your approach to prioritization. Mention setting deadlines, breaking tasks into smaller steps, and using tools such as calendars or project management software. Emphasize adaptability and the ability to re-evaluate priorities as needed.

Example

“I prioritize tasks based on urgency, impact, and dependencies and use a combination of time-blocking techniques and task lists to allocate time. I also regularly communicate with stakeholders to ensure our priorities are aligned and adjust my schedule accordingly. This proactive approach helps me stay organized and focused, even when I have multiple deadlines.”

5. Give an example of when you resolved a conflict on the job.

Interpersonal skills and the ability to handle conflict constructively are essential in a collaborative work environment like BP.

How to Answer

Describe a specific conflict, focusing on your approach to resolution, active listening, empathy, and collaboration. Highlight the positive outcome and any lessons learned from the experience.

Example

“I once had a disagreement with a team member about project priorities. Instead of escalating the conflict, I initiated a one-on-one discussion to understand their perspective and concerns. Through active listening and empathetic communication, we identified common ground and developed a mutually acceptable solution that addressed each of our priorities. This experience reinforced the importance of open communication and collaboration in resolving conflicts.”

6. Given a table of students and their SAT scores, write a query to return the two students with the closest test scores with the score difference.

If multiple students have the same minimum score difference, select the student name combination higher in the alphabet.

Example:

Input:

scores table

Column	Type
id	INTEGER
student	VARCHAR
score	INTEGER

Output:

Column	Type
one_student	VARCHAR
other_student	VARCHAR
score_diff	INTEGER

Through this question, the interviewer will evaluate your ability to write SQL queries to solve a problem, testing your understanding of SQL functions and operations.

How to Answer

Write an SQL query that selects the two students with the minimum absolute difference between their SAT scores. Break ties by choosing student names alphabetically.

Example

SELECT
    s1.student AS one_student
    , s2.student AS other_student
    , ABS(s1.score - s2.score) AS score_diff
FROM scores AS s1
INNER JOIN scores AS s2
    ON s1.id != s2.id
        AND s1.id < s2.id
ORDER BY 3 ASC, 1 ASC
LIMIT 1

7. Let’s say you’re working in HR at a major tech company. They ask you to find employees with a high probability of leaving the company and tell you they perform well but have the lowest pay.

Given two tables, employees and projects, find the five lowest-paid employees who have completed at least three projects.

Note: We consider projects to be completed when they have an end date, which is the same as saying their End_dt is not NULL.

Example:

Input:

employees table

id	salary
INTEGER	FLOAT

projects table

employee_id	project_id	Start_dt	End_dt
INTEGER	INTEGER	DATETIME	DATETIME

Output:

employee_id
INTEGER

As a data analyst candidate at BP, your SQL skills in data retrieval and filtering based on specific criteria will be evaluated with this question. It also tests your understanding of the business context and your ability to translate requirements into SQL queries.

How to Answer

Write an SQL query that identifies employees who perform well (completed at least three projects) but have the lowest salary. Ensure projects are completed (End_dt is not NULL).

Example

SELECT
    p.employee_id
FROM employees e
INNER JOIN projects p
ON
    e.id = p.employee_id
GROUP BY
    e.id
HAVING
    COUNT(p.End_dt) >= 3
ORDER BY
    e.salary ASC
LIMIT 5

8. Given a users table, write a query to return only its duplicate rows.

Example:

Input:

users table

Column	Type
id	INTEGER
name	VARCHAR
created_at	DATETIME

This question evaluates your ability to identify duplicate records in a database table using SQL.

How to Answer

Write an SQL query that identifies duplicate rows in the users table based on all columns.

Example

SELECT
	id,
	name,
	created_at
FROM (
	SELECT
		*,
		row_number() OVER
			(PARTITION BY id ORDER BY created_at ASC)
			AS ranking
	FROM
		users) AS u
WHERE
	ranking > 1

9. Given an employees and departments table, select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over $100,000.

Example:

Input:

employees table

Columns	Type
id	INTEGER
first_name	VARCHAR
last_name	VARCHAR
salary	INTEGER
department_id	INTEGER

departments table

Columns	Type
id	INTEGER
name	VARCHAR

Output:

Column	Type
percentage_over_100k	FLOAT
department_name	VARCHAR
number_of_employees	INTEGER

This question will check your SQL skills in data aggregation, filtering, and ranking based on specific conditions, skills necessary for data analysts at BP.

How to Answer

Write an SQL query that calculates the percentage of employees in each department making over $100,000 in salary and selects the top 3 departments with at least ten employees.

Example

SELECT AVG(CASE WHEN salary > 100000
        THEN 1 ELSE 0 END) AS percentage_over_100k
      , d.name as department_name
      , COUNT(*) AS number_of_employees
FROM departments AS d
LEFT JOIN employees AS e
    ON d.id = e.department_id
GROUP BY d.name
HAVING COUNT(*) >= 10
ORDER BY 1 DESC
LIMIT 3

10. Given the employees and departments table, write a query to get the top 3 highest employee salaries by department. If the department contains less than 3 employees, the top 2 or the top 1 highest salaries should be listed (assume each department has at least 1 employee).

Note: The output should include the employee’s full name in one column, the department name, and the salary. It should be sorted by department name in ascending order and salary in descending order.

Example:

Input:

employees table

Column	Type
id	INTEGER
first_name	VARCHAR
last_name	VARCHAR
salary	INTEGER
department_id	INTEGER

departments table

Column	Type
id	INTEGER
name	VARCHAR

Output:

Column	Type
employee_name	VARCHAR
department_name	VARCHAR
salary	INTEGER

Similar to the previous problem, this question evaluates your SQL skills in data retrieval, sorting, and handling edge cases.

How to Answer

Write an SQL query that selects the top 3 highest employee salaries by department. Use a CASE statement to handle departments with fewer than 3 employees.

Example

WITH employee_ranks AS(
  SELECT
    department_id,
    first_name,
    last_name,
    salary,
    RANK() OVER (PARTITION BY department_id ORDER BY salary DESC) AS ranks
  FROM employees

)

SELECT
  CONCAT(er.first_name,' ', er.last_name) AS employee_name,
  d.name AS department_name,
  salary
FROM employee_ranks er
LEFT JOIN departments d ON d.id=er.department_id
WHERE ranks < 4
ORDER BY department_name ASC, salary DESC

11. How does the WHERE clause differ from the HAVING clause in SQL? Give an example of where each would be appropriate.

This question evaluates your understanding of SQL query syntax and your ability to differentiate between filtering rows using the WHERE clause and filtering groups using the HAVING clause.

How to Answer

You can explain that the WHERE clause filters rows based on specified conditions before any groupings are applied, while the HAVING clause filters groups after the GROUP BY operation has been performed.

Example

“If I want to retrieve sales data for a specific product category such as ‘Electronics,’ I would use the WHERE clause like this: SELECT * FROM sales WHERE category = 'Electronics.' In contrast, if I want to find product categories with total sales exceeding a certain threshold, say $10,000, I would use the HAVING clause: SELECT category, SUM(sales_amount) FROM sales GROUP BY category HAVING SUM(sales_amount) > 10000.”

12. What is a subquery in SQL? Provide an example of how you might use a subquery in a SELECT statement.

Your BP data analyst interviewer is checking your understanding of subqueries and your ability to incorporate them into SQL queries.

How to Answer

Define a subquery as a query nested within another query and explain its purpose in providing a set of data for use in the main query.

Example

“A subquery can be used to retrieve specific information based on the results of another query. For example, to find employees who earn more than the average salary in the company, we could use a subquery like this: SELECT * FROM employees WHERE salary > (SELECT AVG(salary) FROM employees).”

13. Explain the difference between UNION and UNION ALL in SQL. When would you use one over the other?

As a data analyst candidate, your knowledge of SQL set operations and your ability to discern when to use UNION or UNION ALL based on specific requirements is being assessed with this question.

How to Answer

Explain that both UNION and UNION ALL are used to combine the results of two or more SELECT statements, but UNION removes duplicate rows while UNION ALL includes all rows, including duplicates.

Example

“If we want to combine the results of two queries but want to eliminate duplicate rows, we would use UNION. For instance, SELECT product_id FROM table1 UNION SELECT product_id FROM table2.

On the other hand, if we want to include all rows from both queries, including duplicates, we would use UNION ALL. For example, SELECT product_id FROM table1 UNION ALL SELECT product_id FROM table2.”

14. Suppose you’re given a dataset containing sales transactions. How would you approach analyzing this data to identify trends or patterns?

This question checks your analytical skills and ability to develop a systematic approach to data analysis.

How to Answer

You can discuss steps such as data cleaning, exploratory data analysis (EDA), visualization techniques, statistical analysis, and, if applicable, the use of machine learning algorithms.

Example

“First, I would clean the dataset by handling missing values, outliers, and inconsistencies. Then, I would perform an EDA to understand the distribution of sales, identify key metrics, and visualize trends using charts or graphs. I would conduct statistical analysis to detect patterns or correlations between variables. Finally, if necessary, I would apply machine learning models like regression or time series analysis to forecast future sales based on historical data.”

15. Imagine you’re tasked with forecasting future sales for a product. What factors would you take into account, and what techniques would you use for forecasting?

With this question, your BP data analyst interviewer is evaluating your understanding of forecasting methods and your ability to identify relevant factors affecting sales.

How to Answer

Mention factors like historical sales data, seasonality, market trends, economic indicators, promotional activities, and external factors. Techniques may include time series analysis, regression analysis, exponential smoothing, or machine learning models.

Example

“For forecasting future sales, I would consider factors such as historical sales data, seasonality, marketing campaigns, competitor activities, and economic conditions. I might use techniques like time series analysis, specifically ARIMA or SARIMA models, to capture seasonality and trend patterns in the data. Additionally, I could incorporate external variables like weather data or demographic information into a regression model to improve accuracy.”

16. What is normalization in the context of relational databases? Why is it important?

As a data analyst, your understanding of database design principles and the importance of normalization in maintaining data integrity and reducing redundancy will be evaluated with this question.

How to Answer

Define normalization as organizing data in a database to minimize redundancy and dependency by dividing large tables into smaller, related tables and establishing relationships between them. Explain its importance in improving database efficiency, reducing data anomalies, and facilitating data management and scalability.

Example

“Normalization in relational databases involves organizing data into tables and establishing relationships between them to eliminate redundancy and dependency. By breaking down larger tables into smaller, related ones and reducing data duplication, normalization improves data integrity, reduces storage space, and simplifies data management. It also helps prevent anomalies such as insertion, update, and deletion anomalies, ensuring the accuracy and consistency of the database.”

17. Given the importance of data security and privacy at BP, how would you ensure that sensitive information is appropriately handled when performing SQL queries or data manipulations?

This question examines your awareness of data security best practices and your ability to implement measures to protect sensitive information during SQL operations, which are critical for a data analyst at BP.

How to Answer

Discuss techniques such as role-based access control (RBAC), encryption, parameterized queries, auditing, and data masking to safeguard sensitive data. Emphasize the importance of adhering to company policies and regulatory requirements such as GDPR or HIPAA.

Example

“To ensure the security and privacy of sensitive information during SQL operations, I would implement role-based access control to restrict access to authorized users based on their roles and responsibilities. Additionally, I would use encryption techniques to protect data at rest and in transit, employ parameterized queries to prevent SQL injection attacks, and enable auditing to track and monitor access to sensitive data. During this, I would keep in mind company policies and regulatory requirements such as GDPR or HIPAA to safeguard personal and confidential information.”

18. BP is increasingly investing in renewable energy sources. How would you use data analytics to assess the impact of these investments on the company’s overall performance and sustainability goals?

This question assesses your ability as a data analyst at BP to use data to evaluate the impact of business decisions, particularly for sustainability and environmental initiatives.

How to Answer

Discuss methods such as data collection, performance metrics development, trend analysis, scenario modeling, and predictive modeling to assess the impact of renewable energy investments on various aspects of BP’s operations, including financial performance, carbon footprint, and sustainability goals.

Example

“To assess the impact of BP’s investments in renewable energy sources, I would first collect relevant data on energy production, consumption, and financial performance. Then, I would develop performance metrics like renewable energy capacity, carbon emissions reduction, and return on investment (ROI) to measure the effectiveness of these investments. Next, I would run a trend analysis to identify patterns and correlations between renewable energy adoption and key performance indicators. Also, I could use scenario modeling to evaluate the potential impact of different investment strategies on BP’s overall performance and sustainability goals. Finally, I might apply predictive modeling techniques to forecast future trends and optimize decision-making regarding renewable energy investments.”

19. BP aims to enhance its operational efficiency in oil exploration and production. How would you apply predictive analytics models to optimize drilling processes and minimize downtime?

With this question, you can demonstrate your ability to apply predictive analytics techniques to improve operational efficiency and reduce downtime in oil exploration and production at BP.

How to Answer

Discuss methods such as predictive maintenance, failure prediction, equipment optimization, and risk analysis using machine learning algorithms and historical operational data.

Example

“To optimize drilling processes and minimize downtime in oil exploration and production, I would apply predictive analytics models to predict equipment failures and schedule proactive maintenance. Using historical operational data, I could train machine learning algorithms to identify patterns and anomalies indicative of impending equipment failures. By continuously monitoring key performance indicators and sensor data from drilling rigs, pumps, and other equipment, the predictive models could alert operators to potential issues before they lead to downtime. Additionally, I would look at factors such as environmental conditions, well complexity, and geological characteristics to optimize drilling strategies and reduce risk.”

20. Describe the difference between correlation and causation. Give an example of each from your own experience or hypothetical situations.

This question evaluates your understanding of statistical concepts and ability to differentiate between correlation, a necessary skill while working as a data analyst at BP.

How to Answer

Define correlation as a statistical measure of the degree to which two variables change together, whereas causation implies that one variable directly influences the other. Emphasize the importance of establishing causation through controlled experiments.

Example

“Correlation refers to the relationship between two variables, where changes in one variable are associated with changes in another variable. For example, there may be a positive correlation between ice cream sales and sunglasses sales during the summer, as warmer weather increases demand for both products. However, this correlation does not imply causation, as buying sunglasses does not directly cause people to buy ice cream.

In contrast, causation implies a cause-and-effect relationship between variables, where changes in one variable directly influence changes in another variable. For instance, conducting a controlled experiment to test the effect of a new fertilizer on plant growth can establish causation if the results consistently show that plants treated with the fertilizer grow taller than those without it, demonstrating a direct causal relationship between the fertilizer and plant growth.”

21. How would you interpret coefficients of logistic regression for categorical and boolean variables?

This question assesses your understanding of how to interpret coefficients in a logistic regression model, specifically for categorical and boolean variables, which is essential for making informed predictions in data analysis tasks.

How to Answer

Explain how the sign and magnitude of the coefficients can be interpreted to understand the relationship between the predictors and the outcome variable. Discuss the importance of careful handling of categorical variables, such as one-hot encoding, to avoid incorrect assumptions in the model. Mention how to interpret the effect of boolean variables and their impact on the outcome probability.

Example

“When interpreting the coefficients of a logistic regression model, I would first look at the sign of the coefficient. A positive sign indicates that, all else being equal, the variable increases the likelihood of the outcome, while a negative sign suggests an inverse relationship. For boolean variables, if the coefficient is positive, a value of 1 would increase the probability of the outcome, whereas a value of 0 would reduce this effect. For categorical variables, I would ensure they are one-hot encoded to avoid any unintended ranking structure. Each encoded category, now a boolean variable, can be interpreted using the same guidelines. The magnitude of the coefficients provides insight into the strength of the relationship, with larger coefficients indicating a stronger effect on the outcome. However, it’s crucial to consider the scale and structure of the variables when comparing their impact.”

22. What are time series models? Why do we need them when we have less complicated regression models?

As a data analyst, your understanding of time series models and the necessity of these models when dealing with data that exhibits autocorrelation will be evaluated with this question.

How to Answer

Describe time series models as specialized models designed to handle data that is influenced by its past values, which is a key feature in many real-world scenarios. Explain why traditional regression models fall short when autocorrelation is present, as they assume no influence of previous data points on current ones. Highlight the importance of time series models, like ARIMA, in controlling for autocorrelation, enabling accurate inference and predictions in time-dependent data.

Example

“Time series models are essential for analyzing data that is influenced by its past values, a common characteristic in datasets like stock prices, weather patterns, or sales figures. Unlike traditional regression models, which assume no autocorrelation, time series models account for the influence of previous data points on current ones. Without this consideration, standard regression models can produce inflated parameter estimates and misleading results. Time series models, such as ARIMA, control for autocorrelation, allowing for valid inferences and more reliable predictions in time-dependent data.”

Familiarity with the role and concepts improves your confidence and ability to answer during the interview. It also allows the interviewer to easily explore your skills in other domains, contributing to further consideration of your employment as a data analyst at BP. Here are a few tips to help you prepare for the role:

Understand the Role and Requirements

Carefully read the job requirements and learn what’s expected of you. Pay attention to specific responsibilities and the data analytics skills required. While at it, identify the pivotal keywords and use them to tailor your CV and cover letter. Furthermore, research BP’s culture and tailor your behavioral answers accordingly.

Master Data Analysis Concepts and Tools

Gain proficiency in commonly used data analytics tools such as Excel for basic data visualization, Python for data manipulation, and SQL for database querying. Diligently answer questions and solve problems with these tools to increase confidence during the data analyst interview.

Brush Up on Statistical Analysis

Refresh your knowledge of statistical concepts, including descriptive and inferential statistics, probability distributions, hypothesis testing, and regression analysis. Ensure you understand these concepts well enough to explain them clearly to the interviewer at BP.

Focus on Data Visualization

Learn to create clear and compelling visualizations to communicate your findings effectively. Practice using tools like Matplotlib and ggplot2 to create charts and graphs.

Simulate Case Studies and Projects

Undertake hands-on projects or case studies related to the energy sector or similar industries. Choose datasets or scenarios that mirror real-world challenges faced by data analysts at BP.

Apply your data analysis skills to derive actionable insights and recommendations from the data. Document your process, methodologies, and findings to showcase your analytical abilities.

Refine Your Communication Skills

Develop your ability to communicate complex technical concepts and analysis results to non-technical stakeholders like investors and clients. Practice refining complex findings into clear actionable insights. Moreover, learn to listen and adapt your communication style according to the specific audience.

Prepare for the Interview

Prepare for the BP data analyst interview by solving a lot of interview questions, including SQL, behavioral, and Excel questions. While practicing the data query problems, be sure you understand the approach and just not the solution. Moreover, participate in our mock interview sessions to grow more confident about your skills and answers.

How much do data analysts at BP make?

Currently, we can’t share a number due to a lack of data points available on the salary of BP data analysts. Let us know if you have any information on the salary of a BP data analyst.

In the meantime, explore our data analyst salary guide to gain insight into industry trends.

Where can I read about other candidates’ experiences as a BP data analyst?

We have a large Slack group where candidates help each other with information about job interviews at various companies, including BP. You can join in and share your interview experiences too!

Does Interview Query have job postings for the BP data analyst role?

Sure! Check out the newest job opportunities listed on our job portal and apply directly. Keep in mind that specific job positions might not always be available.

BP data analyst interview questions is expected to revolve around basic behavioral questions, SQL, statistics, and a few analytics questions. Ensure you have good verbal communication skills to convey the answers. Prepare for the interview by following the tips mentioned. Also, check out our main BP interview guide, where we discuss other BP roles, including data engineer and data scientist.

We’ll be cheering from the sidelines for your BP data analyst interview. Feel free to hang out with us afterward and share your interview experience. We wish you success!